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package phrase;
import io.FileUtil;
import joptsimple.OptionParser;
import joptsimple.OptionSet;
import java.io.File;
import java.io.IOException;
import java.io.PrintStream;
import java.util.Random;
import arr.F;
public class Trainer
{
public static void main(String[] args)
{
OptionParser parser = new OptionParser();
parser.accepts("help");
parser.accepts("in").withRequiredArg().ofType(File.class);
parser.accepts("out").withRequiredArg().ofType(File.class);
parser.accepts("parameters").withRequiredArg().ofType(File.class);
parser.accepts("topics").withRequiredArg().ofType(Integer.class).defaultsTo(5);
parser.accepts("em-iterations").withRequiredArg().ofType(Integer.class).defaultsTo(5);
parser.accepts("pr-iterations").withRequiredArg().ofType(Integer.class).defaultsTo(0);
parser.accepts("threads").withRequiredArg().ofType(Integer.class).defaultsTo(0);
parser.accepts("scale-phrase").withRequiredArg().ofType(Double.class).defaultsTo(5.0);
parser.accepts("scale-context").withRequiredArg().ofType(Double.class).defaultsTo(0.0);
parser.accepts("seed").withRequiredArg().ofType(Long.class).defaultsTo(0l);
parser.accepts("convergence-threshold").withRequiredArg().ofType(Double.class).defaultsTo(1e-6);
parser.accepts("variational-bayes");
parser.accepts("alpha-emit").withRequiredArg().ofType(Double.class).defaultsTo(0.1);
parser.accepts("alpha-pi").withRequiredArg().ofType(Double.class).defaultsTo(0.01);
parser.accepts("agree");
OptionSet options = parser.parse(args);
if (options.has("help") || !options.has("in"))
{
try {
parser.printHelpOn(System.err);
} catch (IOException e) {
System.err.println("This should never happen.");
e.printStackTrace();
}
System.exit(1);
}
int tags = (Integer) options.valueOf("topics");
int em_iterations = (Integer) options.valueOf("em-iterations");
int pr_iterations = (Integer) options.valueOf("pr-iterations");
double scale_phrase = (Double) options.valueOf("scale-phrase");
double scale_context = (Double) options.valueOf("scale-context");
int threads = (Integer) options.valueOf("threads");
double threshold = (Double) options.valueOf("convergence-threshold");
boolean vb = options.has("variational-bayes");
double alphaEmit = (vb) ? (Double) options.valueOf("alpha-emit") : 0;
double alphaPi = (vb) ? (Double) options.valueOf("alpha-pi") : 0;
if (options.has("seed"))
F.rng = new Random((Long) options.valueOf("seed"));
if (tags <= 1 || scale_phrase < 0 || scale_context < 0 || threshold < 0)
{
System.err.println("Invalid arguments. Try again!");
System.exit(1);
}
Corpus corpus = null;
File infile = (File) options.valueOf("in");
try {
System.out.println("Reading concordance from " + infile);
corpus = Corpus.readFromFile(FileUtil.reader(infile));
corpus.printStats(System.out);
} catch (IOException e) {
System.err.println("Failed to open input file: " + infile);
e.printStackTrace();
System.exit(1);
}
if (!options.has("agree"))
System.out.println("Running with " + tags + " tags " +
"for " + em_iterations + " EM and " + pr_iterations + " PR iterations " +
"with scale " + scale_phrase + " phrase and " + scale_context + " context " +
"and " + threads + " threads");
else
System.out.println("Running agreement model with " + tags + " tags " +
"for " + em_iterations);
System.out.println();
PhraseCluster cluster = null;
Agree agree = null;
if (options.has("agree"))
agree = new Agree(tags, corpus);
else
{
cluster = new PhraseCluster(tags, corpus);
if (threads > 0) cluster.useThreadPool(threads);
if (vb) cluster.initialiseVB(alphaEmit, alphaPi);
}
double last = 0;
for (int i=0; i<em_iterations+pr_iterations; i++)
{
double o;
if (agree != null)
o = agree.EM();
else
{
if (i < em_iterations)
{
if (!vb)
o = cluster.EM();
else
o = cluster.VBEM(alphaEmit, alphaPi);
}
else
o = cluster.PREM(scale_phrase, scale_context);
}
System.out.println("ITER: "+i+" objective: " + o);
if (i != 0 && Math.abs((o - last) / o) < threshold)
{
last = o;
if (i < em_iterations)
{
i = em_iterations - 1;
continue;
}
else
break;
}
last = o;
}
if (cluster == null)
cluster = agree.model1;
double pl1lmax = cluster.phrase_l1lmax();
double cl1lmax = cluster.context_l1lmax();
System.out.println("\nFinal posterior phrase l1lmax " + pl1lmax + " context l1lmax " + cl1lmax);
if (pr_iterations == 0)
System.out.println("With PR objective " + (last - scale_phrase*pl1lmax - scale_context*cl1lmax));
if (options.has("out"))
{
File outfile = (File) options.valueOf("out");
try {
PrintStream ps = FileUtil.printstream(outfile);
cluster.displayPosterior(ps);
ps.close();
} catch (IOException e) {
System.err.println("Failed to open output file: " + outfile);
e.printStackTrace();
System.exit(1);
}
}
if (options.has("parameters"))
{
File outfile = (File) options.valueOf("parameters");
PrintStream ps;
try {
ps = FileUtil.printstream(outfile);
cluster.displayModelParam(ps);
ps.close();
} catch (IOException e) {
System.err.println("Failed to open output parameters file: " + outfile);
e.printStackTrace();
System.exit(1);
}
}
if (cluster.pool != null)
cluster.pool.shutdown();
}
}
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